1. Field of the Invention
Generally, the field of the invention relates to the field of quality control. Products inspected and measured by an optical scanner while moving on a production line and they are accepted for use or rejected based on the inspection results.
2. Prior Art
Image processing systems used a great deal in today's product quality control systems. They are replacing human manpower since they have the advantages of higher throughput, better accuracy of inspection, and lower cost
An inspection system contains a light source with a unique wavelength that illuminates the product being inspected. Images of the inspected products are stored in a computer's memory for analysis by means of an algorithm, also stored in the computer's memory.
Lately, the structure of many inspected products has become more complicated and harder to inspect. For example today's printed circuit boards (PCBs) contain more printed lines per inch than a year ago. Wafer sorting and inspection has became much more complicated Therefore there is a need for inspection systems with faster throughput and better accuracy.
Today automated inspection machines analyze images of complicated structures, such as printed circuit boards, wafers, and wires by means of video cameras and computers. The images taken by the video camera are stored in the memory of a computer. Several standards for image acquisition exist, depending on the type of the camera used. RS170, the US standard, uses an image of 491 lines by 649 pixels. The acquisition rate is 30 images per second. There are non-standard cameras with higher rate of image acquisition, or line cameras that use line sensors with a variety of pixel counts.
Complicated products, such as PCBs, need a line-by-line algorithmic image analysis. Detecting defects and bad solder joints in the size range of one pixel, demand analysis of the gray level values of each pixel. This is necessary to assure good performance of the PCB.
Today, line-by-line image analysis algorithms, such as filtering, averaging, edge enhancement techniques, and neighborhood comparison, require a lot of processing time, resulting in low throughput.
Still another method of inspecting images (based on our above patent) uses templates and histograms of a full image. The technique has the advantage of a quick and accurate results as long as the products' structure is not highly complex.
Products with highly complicated structures require highly complicated templates. In the most complicated templates, each of the pixels in the template has a unique gray level value. A template size of 512 horizontal (H).times.512 vertical (V)(=262,144 total pixels) requires that amount of gray level values. The histogram vector is an array of data, of length 262, 144 places, where each data place is represented by 18 bits (the gray level of each pixel). This is stored as 589,824 bytes of data in memory (byte=eight binary bits).
The histogram vector is thus very large. The processing time for histogram analysis is thus also large, reducing the advantage of high-speed processing.